Package index • ordr

‘ordr’ package A unified framework for ordination objects and biplot methods using tidy principles
`ordr` `ordr-package`	ordr package
Functions, classes, and methods Introducing and adapting ordination techniques for the ordr workflow
`lda_ord()` `predict(<lda_ord>)`	Augmented implementation of linear discriminant analysis
`lra()` `print(<lra>)` `screeplot(<lra>)` `biplot(<lra>)` `plot(<lra>)`	Log-ratio analysis
`eigen_ord()` `svd_ord()` `cmdscale_ord()` `cancor_ord()`	Wrappers for lossy ordination methods
Data sets Additional data sets used to illustrate ordination techniques
`glass`	Glass composition data
`qswur_usa`	U.S. university rankings
Tidy ordination The ‘tbl_ord’ class wrapper, with methods for accessing components and for querying and manipulating metadata
`recover_rows()` `recover_cols()` `get_rows()` `get_cols()` `as.matrix(<tbl_ord>)` `recover_inertia()` `recover_coord()` `get_coord()` `get_inertia()` `dim(<tbl_ord>)`	Access factors, coordinates, and metadata from ordination objects
`recover_aug_rows()` `recover_aug_cols()` `recover_aug_coord()` `augment_ord()`	Augment factors and coordinates of 'tbl_ord' objects
`tidy(<tbl_ord>)` `glance(<tbl_ord>)` `fortify(<tbl_ord>)`	Tidiers for 'tbl_ord' objects
`annotation`	Annotate factors of 'tbl_ord' objects
`get_negation()` `revert_negation()` `negate_ord()` `negate_to_first_orthant()`	Negation of ordination axes
`recover_conference()` `get_conference()` `revert_conference()` `confer_inertia()`	Confer inertia to factors of a 'tbl_ord' object
`recover_supp_rows()` `recover_supp_cols()`	Supplement 'tbl_ord' objects with new data
`as_tbl_ord()` `make_tbl_ord()` `is_tbl_ord()` `is.tbl_ord()` `valid_tbl_ord()` `un_tbl_ord()`	A unified ordination object class
`format(<tbl_ord>)` `print(<tbl_ord>)`	Format a tbl_ord for printing
`plot(<tbl_ord>)` `screeplot(<tbl_ord>)` `biplot(<tbl_ord>)`	Plot and biplot methods for 'tbl_ord' objects
`pull_factor()` `pull_rows()` `pull_cols()` `rename_rows()` `rename_cols()` `select_rows()` `select_cols()` `mutate_rows()` `mutate_cols()` `transmute_rows()` `transmute_cols()` `cbind_rows()` `cbind_cols()` `left_join_rows()` `left_join_cols()`	dplyr verbs for tbl_ord factors
`ordinate()`	Fit an ordination model to a data object
Layered grammar for biplots Functions to generate and annotate biplots from ‘tbl_ord’ objects, following the layered grammar of graphics
`coord_rect()` `coord_biplot()`	Cartesian coordinates and plotting window with fixed aspect ratios
`ggbiplot()` `ord_aes()`	Biplots following the grammar of graphics
`stat_rows()` `stat_cols()`	Render plot elements for one matrix of an ordination
`stat_referent()` `ggplot_add(<LayerRef>)`	Transformations with respect to reference data
`stat_bagplot()`	Bagplots
`stat_center()` `stat_star()`	Compute geometric centers and spreads for ordination factors
`stat_chull()` `stat_peel()`	Convex hulls and hull peelings
`stat_cone()`	Conical hull
`stat_depth()` `stat_depth_filled()`	Depth estimates and contours
`stat_projection()`	Project rows onto columns or vice-versa
`stat_rule()` `minpp()` `maxpp()` `minabspp()`	Construct limited rules offset from the origin
`stat_scale()`	Multiply artificial coordinates by a scale factor
`stat_spantree()`	Calculate a minimum spanning tree among cases or variables
`geom_origin()` `geom_unit_circle()`	Marker or unit circle at the origin
`geom_axis()`	Axes through or offset from the origin
`geom_bagplot()`	Bagplots
`geom_interpolation()`	Render interpolation of new rows from columns (or vice-versa)
`geom_isoline()`	Isolines (contour lines)
`geom_lineranges()` `geom_pointranges()`	Intervals depicting ranges, usually about center points
`geom_rule()`	Rulers through or offset from the origin
`geom_text_radiate()`	Text radiating outward from the origin
`geom_vector()`	Vectors from the origin
`theme_scaffold()` `theme_biplot()`	Scaffolding theme
`draw_key_line()` `draw_key_crosslines()` `draw_key_crosspoint()`	Biplot key drawing functions
`ordr-ggproto` `CoordRect` `CoordBiplot` `GeomAxis` `GeomBagplot` `GeomInterpolation` `GeomPointranges` `GeomLineranges` `GeomIsoline` `GeomOrigin` `GeomUnitCircle` `GeomRule` `GeomTextRadiate` `GeomVector` `StatChull` `StatPeel` `StatDepth` `StatDepthFilled` `StatBagplot` `StatCenter` `StatStar` `StatCone` `StatRows` `StatCols` `StatReferent` `StatProjection` `StatRule` `StatScale` `StatSpantree` `StatRowsDensity2d` `StatColsDensity2d` `StatRowsDensity2dFilled` `StatColsDensity2dFilled` `StatRowsEllipse` `StatColsEllipse` `StatRowsBagplot` `StatColsBagplot` `StatRowsCenter` `StatColsCenter` `StatRowsStar` `StatColsStar` `StatRowsChull` `StatColsChull` `StatRowsPeel` `StatColsPeel` `StatRowsCone` `StatColsCone` `StatRowsDepth` `StatColsDepth` `StatRowsDepthFilled` `StatColsDepthFilled` `StatRowsProjection` `StatColsProjection` `StatRowsRule` `StatColsRule` `StatRowsScale` `StatColsScale` `StatRowsSpantree` `StatColsSpantree`	ggproto classes created and adapted for ordr
`geom_rows_point()` `geom_cols_point()` `geom_rows_path()` `geom_cols_path()` `geom_rows_polygon()` `geom_cols_polygon()` `geom_rows_contour()` `geom_cols_contour()` `geom_rows_density_2d()` `geom_cols_density_2d()` `geom_rows_density_2d_filled()` `geom_cols_density_2d_filled()` `geom_rows_text()` `geom_cols_text()` `geom_rows_label()` `geom_cols_label()` `geom_rows_text_repel()` `geom_cols_text_repel()` `geom_rows_label_repel()` `geom_cols_label_repel()` `geom_rows_axis()` `geom_cols_axis()` `geom_rows_bagplot()` `geom_cols_bagplot()` `geom_rows_interpolation()` `geom_cols_interpolation()` `geom_rows_lineranges()` `geom_cols_lineranges()` `geom_rows_pointranges()` `geom_cols_pointranges()` `geom_rows_isoline()` `geom_cols_isoline()` `geom_rows_rule()` `geom_cols_rule()` `geom_rows_text_radiate()` `geom_cols_text_radiate()` `geom_rows_vector()` `geom_cols_vector()`	Convenience geoms for row and column matrix factors
`stat_rows_density_2d()` `stat_cols_density_2d()` `stat_rows_density_2d_filled()` `stat_cols_density_2d_filled()` `stat_rows_ellipse()` `stat_cols_ellipse()` `stat_rows_bagplot()` `stat_cols_bagplot()` `stat_rows_center()` `stat_cols_center()` `stat_rows_star()` `stat_cols_star()` `stat_rows_chull()` `stat_cols_chull()` `stat_rows_peel()` `stat_cols_peel()` `stat_rows_cone()` `stat_cols_cone()` `stat_rows_depth()` `stat_cols_depth()` `stat_rows_depth_filled()` `stat_cols_depth_filled()` `stat_rows_projection()` `stat_cols_projection()` `stat_rows_rule()` `stat_cols_rule()` `stat_rows_scale()` `stat_cols_scale()` `stat_rows_spantree()` `stat_cols_spantree()`	Convenience stats for row and column matrix factors
Class methods Recovery and augmentation methods for ordination model classes
`as_tbl_ord(<cancor_ord>)` `recover_rows(<cancor_ord>)` `recover_cols(<cancor_ord>)` `recover_inertia(<cancor_ord>)` `recover_coord(<cancor_ord>)` `recover_conference(<cancor_ord>)` `recover_supp_rows(<cancor_ord>)` `recover_supp_cols(<cancor_ord>)` `recover_aug_rows(<cancor_ord>)` `recover_aug_cols(<cancor_ord>)` `recover_aug_coord(<cancor_ord>)`	Functionality for canonical correlations
`as_tbl_ord(<cmds_ord>)` `recover_rows(<cmds_ord>)` `recover_cols(<cmds_ord>)` `recover_inertia(<cmds_ord>)` `recover_coord(<cmds_ord>)` `recover_conference(<cmds_ord>)` `recover_aug_rows(<cmds_ord>)` `recover_aug_cols(<cmds_ord>)` `recover_aug_coord(<cmds_ord>)`	Functionality for classical multidimensional scaling objects
`as_tbl_ord(<correspondence>)` `recover_rows(<correspondence>)` `recover_cols(<correspondence>)` `recover_inertia(<correspondence>)` `recover_conference(<correspondence>)` `recover_coord(<correspondence>)` `recover_aug_rows(<correspondence>)` `recover_aug_cols(<correspondence>)` `recover_aug_coord(<correspondence>)`	Functionality for correspondence analysis ('correspondence') objects
`as_tbl_ord(<eigen>)` `recover_rows(<eigen>)` `recover_cols(<eigen>)` `recover_inertia(<eigen>)` `recover_coord(<eigen>)` `recover_conference(<eigen>)` `recover_aug_rows(<eigen_ord>)` `recover_aug_cols(<eigen_ord>)` `recover_aug_coord(<eigen>)` `as_tbl_ord(<eigen_ord>)` `recover_rows(<eigen_ord>)` `recover_cols(<eigen_ord>)` `recover_inertia(<eigen_ord>)` `recover_coord(<eigen_ord>)` `recover_conference(<eigen_ord>)` `recover_aug_coord(<eigen_ord>)`	Functionality for eigen-decompositions
`as_tbl_ord(<factanal>)` `recover_rows(<factanal>)` `recover_cols(<factanal>)` `recover_inertia(<factanal>)` `recover_coord(<factanal>)` `recover_conference(<factanal>)` `recover_supp_rows(<factanal>)` `recover_aug_rows(<factanal>)` `recover_aug_cols(<factanal>)` `recover_aug_coord(<factanal>)`	Functionality for factor analysis ('factanal') objects
`as_tbl_ord(<kmeans>)` `recover_rows(<kmeans>)` `recover_cols(<kmeans>)` `recover_coord(<kmeans>)` `recover_aug_rows(<kmeans>)` `recover_aug_cols(<kmeans>)` `recover_aug_coord(<kmeans>)`	Functionality for k-means clustering ('kmeans') objects
`as_tbl_ord(<lda>)` `as_tbl_ord(<lda_ord>)` `recover_rows(<lda>)` `recover_rows(<lda_ord>)` `recover_cols(<lda>)` `recover_cols(<lda_ord>)` `recover_inertia(<lda>)` `recover_inertia(<lda_ord>)` `recover_coord(<lda>)` `recover_coord(<lda_ord>)` `recover_conference(<lda>)` `recover_conference(<lda_ord>)` `recover_aug_rows(<lda>)` `recover_aug_rows(<lda_ord>)` `recover_aug_cols(<lda>)` `recover_aug_cols(<lda_ord>)` `recover_aug_coord(<lda>)` `recover_aug_coord(<lda_ord>)` `recover_supp_rows(<lda>)` `recover_supp_rows(<lda_ord>)`	Functionality for linear discriminant analysis ('lda') objects
`as_tbl_ord(<lm>)` `recover_rows(<lm>)` `recover_cols(<lm>)` `recover_coord(<lm>)` `recover_aug_rows(<lm>)` `recover_aug_cols(<lm>)` `recover_aug_coord(<lm>)` `recover_aug_rows(<glm>)` `recover_rows(<mlm>)` `recover_cols(<mlm>)` `recover_coord(<mlm>)` `recover_aug_rows(<mlm>)` `recover_aug_cols(<mlm>)` `recover_aug_coord(<mlm>)`	Functionality for linear model objects
`as_tbl_ord(<lra>)` `recover_rows(<lra>)` `recover_cols(<lra>)` `recover_inertia(<lra>)` `recover_coord(<lra>)` `recover_conference(<lra>)` `recover_aug_rows(<lra>)` `recover_aug_cols(<lra>)` `recover_aug_coord(<lra>)`	Functionality for log-ratio analysis ('lra') objects
`as_tbl_ord(<mca>)` `recover_rows(<mca>)` `recover_cols(<mca>)` `recover_inertia(<mca>)` `recover_conference(<mca>)` `recover_coord(<mca>)` `recover_supp_rows(<mca>)` `recover_aug_rows(<mca>)` `recover_aug_cols(<mca>)` `recover_aug_coord(<mca>)`	Functionality for multiple correspondence analysis ('mca') objects
`as_tbl_ord(<prcomp>)` `recover_rows(<prcomp>)` `recover_cols(<prcomp>)` `recover_inertia(<prcomp>)` `recover_coord(<prcomp>)` `recover_conference(<prcomp>)` `recover_aug_rows(<prcomp>)` `recover_aug_cols(<prcomp>)` `recover_aug_coord(<prcomp>)`	Functionality for principal components analysis ('prcomp') objects
`as_tbl_ord(<princomp>)` `recover_rows(<princomp>)` `recover_cols(<princomp>)` `recover_inertia(<princomp>)` `recover_coord(<princomp>)` `recover_conference(<princomp>)` `recover_supp_rows(<princomp>)` `recover_aug_rows(<princomp>)` `recover_aug_cols(<princomp>)` `recover_aug_coord(<princomp>)`	Functionality for principal components analysis ('princomp') objects
`as_tbl_ord(<svd_ord>)` `recover_rows(<svd_ord>)` `recover_cols(<svd_ord>)` `recover_inertia(<svd_ord>)` `recover_coord(<svd_ord>)` `recover_conference(<svd_ord>)` `recover_aug_rows(<svd_ord>)` `recover_aug_cols(<svd_ord>)` `recover_aug_coord(<svd_ord>)`	Functionality for singular value decompositions

Reference

‘ordr’ package

Functions, classes, and methods

Data sets

Tidy ordination

Layered grammar for biplots

Class methods